SDE2 - API Platform
Role Overview
Sarvam's model APIs (LLM, ASR, TTS, Vision, Translate) are how developers and enterprises ship products on our foundation models. Our OpenAI-compatible LLM APIs route every request across multiple model deployments, with streaming, failover, metering, billing, and rate-limiting all part of the same stack. Today it's FastAPI and Python; we're in the middle of rewriting it in Go.
We're hiring a Software Engineer (SDE 2) to own core parts of this platform. The features. The reliability. The performance. This is an IC role.
Key Skills for This Role
Full Job Posting
About the Role
Sarvam's model APIs (LLM, ASR, TTS, Vision, Translate) are how developers and enterprises ship products on our foundation models. Our OpenAI-compatible LLM APIs route every request across multiple model deployments, with streaming, failover, metering, billing, and rate-limiting all part of the same stack. Today it's FastAPI and Python; we're in the middle of rewriting it in Go.
We're hiring a Software Engineer (SDE 2) to own core parts of this platform. The features. The reliability. The performance. This is an IC role.
What You'll Do
Building and evolving the LLM API platform, from the moment a request hits the edge to the response that goes back out
The Python→Go rewrite: building services in Go alongside the existing Python stack, without compromising reliability
Streaming infrastructure: SSE for Chat Completions and Responses, long-lived connections, clean handling of cancellations and client disconnects
Routing and failover: weighted provider chains, retries with backoff, and latency-driven admission control across model deployments
Protocol compatibility: keeping the API faithful to the OpenAI spec across inference servers (vLLM, SGLang, Dynamo) that each behave slightly differently
The commercial layer: metering, billing, and rate-limiting, engineered to the same bar as the model APIs themselves
Performance and reliability for a multi-tenant platform serving long-context agentic and coding workloads
Observability (logging, metrics, tracing), so the team can debug production confidently and quickly
Integration and load testing: the harness that lets us ship fast without breaking customer-facing APIs
Close partnership with the Inference and MLOps teams on production readiness for new model launches
Design-first, documentation-first engineering culture within the team: RFCs before code, decisions written down, no tribal knowledge
What We're Looking For
3+ years building production backend systems
Strong Python in production: asyncio, FastAPI or similar, and services you've built and operated under real load
Working knowledge of Go, or a strong willingness to learn it: you'll work in both languages through the rewrite
Experience building low-latency, multi-tenant backend services
Hands-on experience with streaming systems: SSE or WebSockets, long-lived connections, backpressure
Strong PostgreSQL and Redis fundamentals: schema design, query performance, caching, and rate limiting
Comfort running services on Kubernetes in production
An ownership mindset: you test before you ship, debug production with metrics, logs, and traces, and write the RCA afterwards
Bonus Points
Experience serving or integrating LLMs in production, especially OpenAI-compatible APIs
Familiarity with inference servers (vLLM, SGLang, Dynamo) and latency metrics such as time to first token and inter-token latency
Experience building metering, billing, or usage-based pricing infrastructure
Time at an early- or growth-stage startup: comfort with ambiguity, speed, and ownership
Why Sarvam?
Sarvam is a fast-moving, high talent-density team building full-stack AI for India, working on problems that push the frontiers of AI with real population-scale impact.
Work alongside researchers, engineers, builders, and business leaders who move fast and hold each other to a very high bar
High ownership and high impact, from day one
Everything we do is AI-first, from the way we build and ship to the way we think about problems
You can work on problems that could change how an entire country learns, works, and communicates
If you want to work on problems at the frontier of AI in India, Sarvam is the place to be.
Qualifications
- 3+ years building production backend systems
- Strong Python in production: asyncio, FastAPI or similar, and services you've built and operated under real load
- Working knowledge of Go, or a strong willingness to learn it: you'll work in both languages through the rewrite
- Experience building low-latency, multi-tenant backend services
- Hands-on experience with streaming systems: SSE or WebSockets, long-lived connections, backpressure
- Strong PostgreSQL and Redis fundamentals: schema design, query performance, caching, and rate limiting
- Comfort running services on Kubernetes in production
- An ownership mindset: you test before you ship, debug production with metrics, logs, and traces, and write the RCA afterwards
- Experience serving or integrating LLMs in production, especially OpenAI-compatible APIs
- Familiarity with inference servers (vLLM, SGLang, Dynamo) and latency metrics such as time to first token and inter-token latency
- Experience building metering, billing, or usage-based pricing infrastructure
- Time at an early- or growth-stage startup: comfort with ambiguity, speed, and ownership
- Why Sarvam?
- Sarvam is a fast-moving, high talent-density team building full-stack AI for India, working on problems that push the frontiers of AI with real population-scale impact.
- Work alongside researchers, engineers, builders, and business leaders who move fast and hold each other to a very high bar
- High ownership and high impact, from day one
- Everything we do is AI-first, from the way we build and ship to the way we think about problems
- You can work on problems that could change how an entire country learns, works, and communicates
- If you want to work on problems at the frontier of AI in India, Sarvam is the place to be.
Preferred Qualifications
- Bonus Points
Responsibilities
- Building and evolving the LLM API platform, from the moment a request hits the edge to the response that goes back out
- The Python→Go rewrite: building services in Go alongside the existing Python stack, without compromising reliability
- Streaming infrastructure: SSE for Chat Completions and Responses, long-lived connections, clean handling of cancellations and client disconnects
- Routing and failover: weighted provider chains, retries with backoff, and latency-driven admission control across model deployments
- Protocol compatibility: keeping the API faithful to the OpenAI spec across inference servers (vLLM, SGLang, Dynamo) that each behave slightly differently
- The commercial layer: metering, billing, and rate-limiting, engineered to the same bar as the model APIs themselves
- Performance and reliability for a multi-tenant platform serving long-context agentic and coding workloads
- Observability (logging, metrics, tracing), so the team can debug production confidently and quickly
- Integration and load testing: the harness that lets us ship fast without breaking customer-facing APIs
- Close partnership with the Inference and MLOps teams on production readiness for new model launches
- Design-first, documentation-first engineering culture within the team: RFCs before code, decisions written down, no tribal knowledge
- 3+ years building production backend systems
- Strong Python in production: asyncio, FastAPI or similar, and services you've built and operated under real load
- Working knowledge of Go, or a strong willingness to learn it: you'll work in both languages through the rewrite
- Experience building low-latency, multi-tenant backend services
- Hands-on experience with streaming systems: SSE or WebSockets, long-lived connections, backpressure
- Strong PostgreSQL and Redis fundamentals: schema design, query performance, caching, and rate limiting
- Comfort running services on Kubernetes in production
- An ownership mindset: you test before you ship, debug production with metrics, logs, and traces, and write the RCA afterwards
- Experience serving or integrating LLMs in production, especially OpenAI-compatible APIs
- Familiarity with inference servers (vLLM, SGLang, Dynamo) and latency metrics such as time to first token and inter-token latency
- Experience building metering, billing, or usage-based pricing infrastructure
- Time at an early- or growth-stage startup: comfort with ambiguity, speed, and ownership
- Sarvam is a fast-moving, high talent-density team building full-stack AI for India, working on problems that push the frontiers of AI with real population-scale impact.
- Work alongside researchers, engineers, builders, and business leaders who move fast and hold each other to a very high bar
- High ownership and high impact, from day one
- Everything we do is AI-first, from the way we build and ship to the way we think about problems
- You can work on problems that could change how an entire country learns, works, and communicates
- If you want to work on problems at the frontier of AI in India, Sarvam is the place to be.
About Sarvam AI
Indian sovereign AI company building multilingual models, infrastructure, and AI products for enterprises, governments, and developers.
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